19,148 research outputs found
Postmortem iris recognition and its application in human identification
Iris recognition is a validated and non-invasive human identification technology currently implemented for the purposes of surveillance and security (i.e. border control, schools, military). Similar to deoxyribonucleic acid (DNA), irises are a highly individualizing component of the human body. Based on a lack of genetic penetrance, irises are unique between an individualās left and right iris and between identical twins, proving to be more individualizing than DNA.
At this time, little to no research has been conducted on the use of postmortem iris scanning as a biometric measurement of identification. The purpose of this pilot study is to explore the use of iris recognition as a tool for postmortem identification. Objectives of the study include determining whether current iris recognition technology can locate and detect iris codes in postmortem globes, and if iris scans collected at different postmortem time intervals can be identified as the same iris initially enrolled.
Data from 43 decedents involving 148 subsequent iris scans demonstrated a subsequent match rate of approximately 80%, supporting the theory that iris recognition technology is capable of detecting and identifying an individualās iris code in a postmortem setting. A chi-square test of independence showed no significant difference between match outcomes and the globe scanned (left vs. right), and gender had no bearing on the match outcome. There was a significant relationship between iris color and match outcome, with blue/gray eyes yielding a lower match rate (59%) compared to brown (82%) or green/hazel eyes (88%), however, the sample size of blue/gray eyes in this study was not large enough to draw a meaningful conclusion. An isolated case involving an antemortem initial scan collected from an individual on life support yielded an accurate identification (match) with a subsequent scan captured at approximately 10 hours postmortem.
Falsely rejected subsequent iris scans or "no match" results occurred in about 20% of scans; they were observed at each PMI range and varied from 19-30%. The false reject rate is too high to reliably establish non-identity when used alone and ideally would be significantly lower prior to implementation in a forensic setting; however, a "no match" could be confirmed using another method. Importantly, the data showed a false match rate or false accept rate (FAR) of zero, a result consistent with previous iris recognition studies in living individuals.
The preliminary results of this pilot study demonstrate a plausible role for iris recognition in postmortem human identification. Implementation of a universal iris recognition database would benefit the medicolegal death investigation and forensic pathology communities, and has potential applications to other situations such as missing persons and human trafficking cases
Improved Lower Bounds for Constant GC-Content DNA Codes
The design of large libraries of oligonucleotides having constant GC-content
and satisfying Hamming distance constraints between oligonucleotides and their
Watson-Crick complements is important in reducing hybridization errors in DNA
computing, DNA microarray technologies, and molecular bar coding. Various
techniques have been studied for the construction of such oligonucleotide
libraries, ranging from algorithmic constructions via stochastic local search
to theoretical constructions via coding theory. We introduce a new stochastic
local search method which yields improvements up to more than one third of the
benchmark lower bounds of Gaborit and King (2005) for n-mer oligonucleotide
libraries when n <= 14. We also found several optimal libraries by computing
maximum cliques on certain graphs.Comment: 4 page
Knowledge Rich Natural Language Queries over Structured Biological Databases
Increasingly, keyword, natural language and NoSQL queries are being used for
information retrieval from traditional as well as non-traditional databases
such as web, document, image, GIS, legal, and health databases. While their
popularity are undeniable for obvious reasons, their engineering is far from
simple. In most part, semantics and intent preserving mapping of a well
understood natural language query expressed over a structured database schema
to a structured query language is still a difficult task, and research to tame
the complexity is intense. In this paper, we propose a multi-level
knowledge-based middleware to facilitate such mappings that separate the
conceptual level from the physical level. We augment these multi-level
abstractions with a concept reasoner and a query strategy engine to dynamically
link arbitrary natural language querying to well defined structured queries. We
demonstrate the feasibility of our approach by presenting a Datalog based
prototype system, called BioSmart, that can compute responses to arbitrary
natural language queries over arbitrary databases once a syntactic
classification of the natural language query is made
DNA Computing by Self-Assembly
Information and algorithms appear to be central to biological organization
and processes, from the storage and reproduction of genetic information to
the control of developmental processes to the sophisticated computations
performed by the nervous system. Much as human technology uses electronic
microprocessors to control electromechanical devices, biological
organisms use biochemical circuits to control molecular and chemical events.
The engineering and programming of biochemical circuits, in vivo and in
vitro, would transform industries that use chemical and nanostructured
materials. Although the construction of biochemical circuits has been
explored theoretically since the birth of molecular biology, our practical
experience with the capabilities and possible programming of biochemical
algorithms is still very young
O-GlcNAcase contributes to cognitive function in Drosophila
Contains fulltext :
219183.pdf (publisher's version ) (Open Access
Methyl Coenzyme M Reductase (mcrA) Gene Abundance Correlates with Activity Measurements of Methanogenic H2/CO2-Enriched Anaerobic Biomass
Biologically produced methane (CH4) from anaerobic digesters is a renewable alternative to fossil fuels, but digester failure can be a serious problem. Monitoring the microbial community within the digester could provide valuable information about process stability because this technology is dependent upon the metabolic processes of microorganisms. A healthy methanogenic community is critical for digester function and CH4 production. Methanogens can be surveyed and monitored using genes and transcripts of mcrA, which encodes the Ī± subunit of methyl coenzyme M reductase ā the enzyme that catalyses the final step in methanogenesis. Using clone libraries and quantitative polymerase chain reaction, we compared the diversity and abundance of mcrA genes and transcripts in four different methanogenic hydrogen/CO2 enrichment cultures to function, as measured by specific methanogenic activity (SMA) assays using H2/CO2. The mcrA gene copy number significantly correlated with CH4 production rates using H2/CO2, while correlations between mcrA transcript number and SMA were not significant. The DNA and cDNA clone libraries from all enrichments were distinctive but community diversity also did not correlate with SMA. Although hydrogenotrophic methanogens dominated these enrichments, the results indicate that this methodology should be applicable to monitoring other methanogenic communities in anaerobic digesters. Ultimately, this could lead to the engineering of digester microbial communities to produce more CH4 for use as renewable fuel
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